index int64 0 1,000k | blob_id stringlengths 40 40 | code stringlengths 7 10.4M |
|---|---|---|
991,400 | 9770b437af921f6d213793f94d6a2628f08e8359 | #coding=utf8
from django.shortcuts import render,render_to_response
from django import forms
from django.conf import settings
from django.shortcuts import redirect
from django.http import HttpResponse,HttpResponseRedirect
from django.template import RequestContext
from django.contrib.auth import authenticate,login
from... |
991,401 | e7aa8d577042225c13a876d3721d017b9251b748 | import json
import requests
def joke():
URL = requests.get('https://v2.jokeapi.dev/joke/Programming,Miscellaneous,Dark,Pun,Spooky')
JSON_URL = URL.json()
if JSON_URL["type"] == "twopart":
print(JSON_URL["setup"])
print(JSON_URL["delivery"])
elif JSON_URL["type"] == "single":
print(JSON_URL["joke"])
... |
991,402 | f9c7b28f35bfc68c885856ee2470da86589e6687 | """
Question:
Please write a program using generator to print the numbers which can be divisible by 5 and 7 between 0 and n in comma separated form while n is input by console.
Example:
If the following n is given as input to the program:
100
Then, the output of the program should be:
0,35,70
Hints:
Use yield to ... |
991,403 | 418b348d31fadc2857df0bc4c04d964cdc7a1baf | #!/usr/bin/env python
import logging
import sys
from sklearn.feature_extraction.text import CountVectorizer
from sentiment_analysis.make_dataset import read_dataset
from sentiment_analysis.utils import write_pickle
def make_bag_of_words_features(
corpus_dataset_path,
training_dataset_path,
... |
991,404 | cf59ee21080d1e56a2a36f8f382dd9eb82570683 | import nltk
import collections
from nltk import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer
import numpy as np
from pptx import Presentation
import os
def prcoss(tokens):
count = nltk.defaultdict(int)
for word in tokens:
count[word] += 1
return count
def c... |
991,405 | 6df514e1662f986aee9e324d5a0479bbdcfaeec4 | from __future__ import print_function
from __future__ import absolute_import
import random
from .utils import rand_max
import copy
from .graph import StateNode
class MCTS(object):
"""
The central MCTS class, which performs the tree search. It gets a
tree policy, a default policy, and a backup strategy.
... |
991,406 | 6cd56359a2d5491b58dd5f061c39b1782a03feb3 | from .entity import Entity
from .weapon import Weapon
from ..tools import sf, gen_texture
class Ship(Entity):
def __init__(self, x=20, y=20):
texture = gen_texture(x, y)
super().__init__(texture)
self.weapon = Weapon()
def shoot(self, board):
projectile = self.weapon.use(self.... |
991,407 | 6044e0f4ebb3537e5d50988ce854700ea540f104 | import numpy as np
import cv2
import pyrealsense2 as rs
from ORB_VO.pso import PSO
THRESHHOLD = 30
FEATUREMAX = 200
INLIER_DIST_THRE = 10
class Optimizer:
def __init__(self, featureA, featureB, matches, intrin):
self.featureA = featureA
self.featureB = featureB
self.matches = matches
... |
991,408 | 21bf0e36a823c29119142c5ef199a2b14ec3ca3b | import torch.nn.functional as F
from torch import nn
from torchvision import models
class SegNet(nn.Module):
def __init__(self, num_classes, pretrained=False, fix_weights=False):
super(SegNet, self).__init__()
self.name = "true_segnet"
self.num_classes = num_classes
# vgg = models.... |
991,409 | 331e262af450ca3ddd3df3a68d4af10ad828bffe | # SECTION PROCESS - Processes command line arguments.
# =====================================================
def resolve(args = [], type = ''):
# Get the index of the type to resolve
index = {'command': 0, 'argument': 1}[type]
# Ensure the args list has enough items
if len(args) > index:
# Return the item... |
991,410 | 2b9d4ef4683908f662c5ea1e05a8e7261df1991a | from rest_framework import viewsets
from .models import Restaurant
from .serializers import RestaurantSerializer
from rest_framework.permissions import AllowAny, IsAuthenticated
from rest_framework.response import Response
from rest_framework.decorators import action
class RestaurantViewSet(viewsets.ModelViewSet):
... |
991,411 | 8268108044f9b1abe5153e912348d139601fa44d | from preprocess.load_data.data_loader import load_hotel_reserve
customer_tb, hotel_tb, reserve_tb = load_hotel_reserve()
# 下の行から本書スタート
# 予約回数を計算(「3-1 データ数、種類数の算出」の例題を参照)
rsv_cnt_tb = reserve_tb.groupby('hotel_id').size().reset_index()
rsv_cnt_tb.columns = ['hotel_id', 'rsv_cnt']
# 予約回数をもとに順位を計算
# ascendingをFalseにすること... |
991,412 | 82619ab5ee680d769095c69db3915a0d20da96c5 |
MOD = 10 ** 9 + 7
import math
__author__ = 'Danyang'
class Solution(object):
def solve(self, cipher):
N, M = cipher
return math.factorial(N + M - 1) / math.factorial(N) / math.factorial(M - 1) % MOD
if __name__ == "__main__":
import sys
f = open("1.in", "r")
testcase... |
991,413 | bbffff9dbe29982994c8edd101db86dc44786d6c | """
This module is one of the two entrypoints with train.py
It is used to make predictions using our model.
"""
import pickle
import logging
from typing import Union
from warnings import simplefilter
import pandas as pd
from pandas.core.common import SettingWithCopyWarning
import src.config.base as base
impo... |
991,414 | d643a01e1f285780f20512c7809f0f316c1692bf | from typing import Iterable, Tuple, List, Callable, Union
from Day02.task import Mode, IntMachine, CustomList, work_code
from Day17.task import my_machine
from Day19 import INPUT
from helper import Iterator, Point, get_all_combs
from main import custom_print as custom_printer
def get_affected_pos(inp: Union[List[int... |
991,415 | 6176bddc84b89b27a561db0c83faa9280d9f890a | import pandas as pd
from sqlalchemy import create_engine
from util.scrawl import *
import os
def repay():
engine = create_engine('mysql+pymysql://root:gkd123,.@47.101.44.55:3306/Houseprice?charset=utf8', encoding='utf-8')
df = pd.read_sql('select * from infodata', engine)
cc = 0
for index, row in df.it... |
991,416 | 5c738e0743d4960ebbefb62c4b405691136ed54c | #To add elements to a set using- add()
#Initially colors is an empty set
colors = set()
print(colors) #set()
colors.add('blue')
colors.add('red')
colors.add('white')
print(colors) #{'blue... |
991,417 | 90c3d457c3a902d7dd2077b46f17985f156a67bc | import vgg
import numpy as np
import tensorflow as tf
import cv2
import os
import wrapper
from functools import reduce
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
def gram_matrix(matrix):
return np.matmul(matrix.T,matrix)/matrix.size
content_layers = ('relu3_2','relu4_2', 'relu5_2')
style_layers = ('relu1_1', 'relu2... |
991,418 | af039bcd7cffec5e8ab7b598bd7a01ab52338848 | print("hello world")
# comment : 메모 적어두는 곳
# variables : 변수 = "변하는 수"
identity = 'pencil'
print('I want to write it by',identity,'.')
# 변수의 종류는 크게 두 가지 있음: 숫자와 문자열 변수로 나뉨. 이걸 변수의 data type이라고 함. 정수와 실수, 문자열 data type이라고 함. int, double (or float), string
a = 5
b = 1.1
c = 'hello'
# 숫자 변수는 사칙연산이 가능, 문자 변수는 불가능
a = a+1... |
991,419 | 38d8f397a82b278fd1d22d6a80f26c3fe7e8b0bf | from dynamixel_sdk.port_handler import *
from dynamixel_sdk.packet_handler import *
from colors import *
class ModelFlag:
def __init__(self, address, data_length):
self.address = address
self.data_length = data_length
class Dynamixel:
protocol_versions = [1.0, 2.0]
models = {
# M... |
991,420 | 98b75bc712ef8c65d8a67310e4083d7f4b502d1e | #
# Copyright (C) University College London, 2007-2012, all rights reserved.
#
# This file is part of HemeLB and is CONFIDENTIAL. You may not work
# with, install, use, duplicate, modify, redistribute or share this
# file, or any part thereof, other than as allowed by any agreement
# specifically made by you with Un... |
991,421 | 8de4db3f673ee5d3a17bae14c9cac1d4e7810c76 | import numpy as np
import pandas as pd
from sklearn.pipeline import Pipeline
from sklearn.model_selection import GridSearchCV
import six
class MLModelPipeline:
def __init__(self, process_features, feature_selection, clf):
self.process_features = process_features
self.feature_selection = feature_... |
991,422 | 528536c9c99a40a08783ef5f68b2a99a92da3aad | from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
import sys
import numpy as np
import parsebmp as pb
# Define method
def weight_variable(shape, name):
initial = tf.truncated_normal(shape, stddev=0.1)
return tf.Variable(initial, name=name)
def bias_variable(shape, name):
initial... |
991,423 | 72c5a0e2ccee849db3dc473298e59067f622e535 | #-*- coding:utf-8 -*-
#!/usr/bin/env python
import os
import sys
import datetime
import logging
import enviroment
from daemon import run_daemon
from time import sleep
# 启动真正的运行进程
def start_server_in_subprocess():
import http.server as root_server
logging.info('server start.')
root_server.start_http_serve... |
991,424 | 0d5e4bbe3f782f1bf1a8db2e2dcd24e0d7cd1467 | import traceback
import os
import boto3
from botocore.exceptions import ClientError # , EndpointConnectionError
def handleRecord(decoded_line):
send = False
cur_region = os.environ["AWS_REGION"]
try:
confirm = os.environ["CONFIRM_INSTANCES"]
except KeyError:
# Default to confirm the i... |
991,425 | 6b9c32517548ff907fc7dc4a70db3ddd55076c84 | def hello():
return "world"
def test_hello():
assert hello() == "world"
|
991,426 | 433915870ed0252c02209e2da7c846a80dfc9394 | # The MIT License (MIT)
# Copyright (c) 2018 by the ESA CCI Toolbox development team and contributors
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of
# this software and associated documentation files (the "Software"), to deal in
# the Software without restriction, including without ... |
991,427 | 5a64663eac9081e21b38069579274cae7cfedafc | # -*- coding: utf-8 -*-
# @Time : 2019/1/9 15:24
# @Author : Junee
# @FileName: 868二进制间距.py
# @Software : PyCharm
# Observing PEP 8 coding style
class Solution(object):
def binaryGap(self, N):
"""
:type N: int
:rtype: int
"""
N = list(str(bin(N)))
... |
991,428 | 88817ca6c6134942e50c4aff91738c514d92ecaa | import email, smtplib, ssl
from email import encoders
from email.mime.base import MIMEBase
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
class SendMail():
def __init__(self, content):
# Create a multipart message and set headers
password = content["password"]... |
991,429 | b36ae566985cf16ac84f23c608db0de26c8506be | from django.db import models
from django.contrib.auth.models import User
from django.db.models.signals import post_save
from django.dispatch import receiver
# Create your models here.
class User_profile(models.Model) :
ezpdf_user = models.OneToOneField(User , on_delete = models.CASCADE)
folder_id = models.Ch... |
991,430 | 49f4b2fa5c0332989c09610b2f8ea5e8e14490f4 | from mworks.conduit import *
import time, sys
client = IPCClientConduit("python_bridge_plugin_conduit")
def hello_x(evt):
print("got evt")
print("evt.code = %i" % evt.code)
print("evt.data = %d" % evt.data)
print("evt.time = %i" % evt.time)
client.initialize()
client.register_callback_for_name... |
991,431 | 33f44572032eed73e9ee7fd655af110a744eac7b | #token
TOKEN = '732030625:AAHXvNnqwLREd1u6-nIyXqX_ZfL2PbKmwAA'
#language
from bot import rus_text
from bot import eng_text
DEFAULT_LANGUAGE = 'ru'
TEXT = {
'ru': rus_text,
'ENG': eng_text
}
|
991,432 | 08ec9397be6530c5a0095952df8ad61d71107444 | '''
Constants Module
'''
''' Hue/Intensity Gesture Skin Detector Constants'''
class SkinCons(object):
HUE_LT = 3
HUE_UT = 50
INTENSITY_LT = 15
INTENSITY_UT = 250
''' Three Gesture Constants - Depth Lowerbound/UppperBound; Area Lowerbound/UppperBound'''
class GesConsAttributes(object):
pass
cl... |
991,433 | 6d33ac5cab71eda9d44e62e0757e75a32d31bcc8 | import io
import numpy as np
import os
import pygtrie
import tempfile
# shared global variables to be imported from model also
UNK = "$UNK$"
NUM = "$NUM$"
NONE = "O"
# special error message
class MyIOError(Exception):
def __init__(self, filename):
# custom error message
message = """
ERROR: Unab... |
991,434 | 087f988cf63b9fb3b4470989f6f89698b4c92bea | '''
Read all the actorlogins csv files saved in the actorlogin
dir and extract all the unique user actorlogins along with
how many times each user interacted with the github
platform. After extracting this information save it into a
unique users file.
(ONE TIME EXECUTION)
'''
import os
csv_files = [x for x in os.lis... |
991,435 | 94ea4dd4c163d3840e2105f2ea2eb00c04127141 | #!/usr/bin/env python
import shelve
import numpy as np
import sys
from rnarry.sequtils import GiantFASTAFile
from rnarry.sequtils import reverse_complement
from rnarry.utils import textwrap
from rnarry.bxwrap import MultiTrackSplitBinnedArray
MINREADSTOCALL = 10
MINPERCENTTOCALL = 0.9
blklength = lambda blks: sum(end... |
991,436 | 7f15a1c532d9a6f1d7aa4e255b381f2316219d31 | # -*- coding: utf-8 -*-
class Card:
SUITS = ['S', 'H', 'D', 'C']
RANKS = ['6', '7', '8', '9', '10', 'J', 'Q', 'K', 'A']
SUITS_PRINTABLE = ['♠', '♥', '♦', '♣']
def __init__(self, suit, rank):
self.suit = suit;
self.rank = rank;
def __repr__(self):
return self.rank + self.pri... |
991,437 | 184064077c31493900d49abe8e8fd49481c8e0c4 | '''
Created on Mar 27, 2019
@author: dsj529
'''
import numpy as np
import pandas as pd
from pandas.plotting import scatter_matrix
from matplotlib import pyplot as plt
from sklearn import model_selection, preprocessing
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC
from sklearn.metrics i... |
991,438 | b2822f2b6386413e7fc2bc143befa5f1de55d9d8 | import random
def guess():
number = random.randint(1, 20)
attempt = 0
while (attempt != number):
print('Take a guess')
attempt = int(input())
if (attempt < number):
print('Too low.')
elif (attempt > number):
print('Too high.')
else:
break
print('Good job.')
print('I am thinking of a number be... |
991,439 | 2a82b2c70ea7f3e3472c0a03069dad0222774c06 | import os
to_split_fn = '/afs/csail.mit.edu/u/t/tzhan/eeg/patient_file_lists/largest/patient_largest_files_whole.txt'
output_fn = '/afs/csail.mit.edu/u/t/tzhan/eeg/patient_file_lists/largest/hosp_largest_files.txt'
# Number of files to split each hospital into
split_n = 2
def chunkIt(seq, num):
# split list into 'n' ... |
991,440 | 5f381e7fde408830df2c4f73bf3137d4c5ad6e79 | import uhal
uhal.disableLogging()
hw_man = uhal.ConnectionManager("file://connection.xml")
amc13 = hw_man.getDevice("amc13")
# reset AMC13 (necessary for daq link to be ready after reset of WFD)
amc13.getNode("CONTROL0").write(0x1)
amc13.dispatch()
|
991,441 | 94e10aab9145a2b9e206e211a7c812d0a9303002 | #! /usr/bin/env python
from __future__ import print_function
from PyQt4 import QtCore,QtGui
from PyQt4.QtOpenGL import *
from OpenGL.GL import *
from OpenGL.GLU import *
import time
import numpy
import math
import os, sys
import Texture
def distance(x1,y1,x2,y2):
dx = x1 - x2
dy = y1 - y2
return math.sqrt(dx*... |
991,442 | 4c15792d1105b57e5e11042bc7949ad77b8bff32 | import io
import tarfile
import textwrap
import sys
SCRIPT_TEMPLATE= """#!/usr/bin/env python
from distutils.core import setup
setup(name='{name}',
version='1.0',
)
try:
{script}
except Exception as e:
print(e)
"""
DEFAULT_SCRIPT = """print(42)"""
def build_setup(script, name):
script_body = textwrap.in... |
991,443 | 485609f6d3dc345b05149c00ee62e2c6e41b7fd0 | n = int(input())
initial = 5
total = 0
for i in range(n):
liked = initial//2
total+=liked
initial = liked*3
print(initial,liked,total)
|
991,444 | 5a02ed9788a12d065aca99c098dec2579f7e0c6f | import json
import requests
from song import Song
class SpotifyRecom:
def __init__(self, token):
self.token = token
def get_last_played_tracks(self, limit=10):
url = f"https://api.spotify.com/v1/me/player/recently-played?limit={limit}"
response = self._place_get_api_request(url)
... |
991,445 | 33bcab25b344966d173bbce74e37cbd3bb29b72e | from __future__ import unicode_literals
from django.utils.encoding import python_2_unicode_compatible
from django.db import models
from django.contrib.postgres.fields import ArrayField
import os
@python_2_unicode_compatible
class Classes(models.Model):
letter_yr = models.CharField(max_length=2, primary_key=True)
... |
991,446 | 4db9f5dd32f67d70e42e20a62bf70db08ccb2fa6 | '''
Created on Aug 25, 2014
@author: Changlong
'''
import zmq
import threading
import struct
import logging
import datetime
import time
import traceback
from twisted.internet import threads
from twisted.internet.defer import DeferredLock
from DB import SBDB, SBDB_ORM
# from SBPS import ProtocolReactor
from Utils impo... |
991,447 | 27dcd3afb436a08c860bfb7743404fbfffbbaed3 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Application de SoundBoard avec interface Qt
======================
Exécuter pour commencer l'utilisation de la SoundBoard.
"""
import json
from PySide2.QtCore import (QRect, QSize)
from PySide2.QtWidgets import (
QApplication, QDialog, QVBoxLayout, ... |
991,448 | 0a7268804c61247fef6dc0f3a7c45afad00f08fc | class Solution:
def solve(self, input, N):
spoken_map, last_spoken = {}, None
for i in range(len(input)):
spoken_map[input[i]] = i + 1,
n = len(input)
last_spoken = input[n - 1]
while n < N:
n += 1
if len(spoken_map[last_spoken]) == 1:
... |
991,449 | 196dcd51b8ab6b83133af71bc040fc165d0c3b64 | k = [1, 2, 3, 4, 5]
# increment the 3rd element
def increment(list):
list[2] += 10
print(list)
increment(k)
|
991,450 | 6d3eb6811ee25bbda22be7945e0c252fef228a86 | # Imports
import pandas as pd
import requests
import re
from bs4 import BeautifulSoup, SoupStrainer
import selenium
from selenium import webdriver
import time
import getpass
import matplotlib.pyplot as plt
import seaborn as sns
#################### Analyze and Plot ####################
sns.set_style("white")
sns.se... |
991,451 | 4140027e7565e537f78a9fee760e751d267092f6 | # -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from pandas import DataFrame,Series
#from sklearn.cross_validation import train_test_split
from sklearn.model_selection import KFold, cross_val_score as CVS, train_test_split as TTS
#from sklearn.linear_model import Li... |
991,452 | 03f3ebbb9adde4410ffa55623f3ec184a1edfb47 | from nc8.instruction import Instruction
import nc8.conversions
class JumpInstruction(Instruction):
def __init__(self):
super(JumpInstruction, self).__init__('jmp',
base_opcode=0xc0,
argument_range=(0, 0xf),
... |
991,453 | 5ac9e5b04ff5854301be7ac2fbac597abb62531c | #-*- coding: utf-8 -*-
from copy import deepcopy
from django.contrib import admin
from mezzanine.pages.models import RichTextPage
from mezzanine.pages.admin import PageAdmin
from mezzanine.blog.admin import BlogPostAdmin
from mezzanine.blog.models import BlogPost
from .models import *
HomePage_fieldsets = deepcopy(Pa... |
991,454 | d4c534f889a528f4922048c885c1f2488bcdbe17 |
from xai.brain.wordbase.nouns._loincloth import _LOINCLOTH
#calss header
class _LOINCLOTHS(_LOINCLOTH, ):
def __init__(self,):
_LOINCLOTH.__init__(self)
self.name = "LOINCLOTHS"
self.specie = 'nouns'
self.basic = "loincloth"
self.jsondata = {}
|
991,455 | 0cd5a2f55bb009f3baebe3da3b4f32daccc57bb0 | # ==================================================================================
# File: deviceclient.py
# Author: Larry W Jordan Jr (larouex@gmail.com)
# Use: Created and send telemetry to Azure IoT Central with this persisted
# device client
#
# https://github.com/Larouex/cold-hub-azure-iot... |
991,456 | 4e7432471668218a7d6c180aef830a7fa70d79b3 | import geopandas as gpd
from shapely.geometry import Polygon
#lat_point_list = [-16.2, -16.2, -19.4, -19.4, -16.2]
#lon_point_list = [ 176.4, 179.1, 179.1, 176.4, 176.4]
#lat_point_list = [ -17.2982, -17.2982, -18.3024, -18.3024, -17.2982 ]
#lon_point_list = [ 177.3083, 178.6267, 178.6267, 177.3083, 177.3083 ]
lat_p... |
991,457 | abdd26a91cded96378c8d8a832a976423e8a1035 | import torch
import torch.nn as nn
import torch.nn.functional as F
import scipy.ndimage as ndimage
class FocalLoss3d_ver1(nn.Module):
def __init__(self, gamma=2, pw=10, threshold=1.0, erode=3, backzero=0):
super().__init__()
self.gamma = gamma
self.pw=pw
self.threshold=threshold
... |
991,458 | 9b26d506029353748090fd9ba1ddaa26105a4035 | from django.conf.urls import url, include
from django.contrib import admin
from django.conf.urls.static import static
from django.conf import settings
urlpatterns = [
url(r'^admin/', admin.site.urls),
# Project apps
url(r'^first-draft/', include('apps.first_draft.urls', namespace='first-draft')),
]
if s... |
991,459 | 5c32c15b9d72150894a40499573c9098bb6f2c8d | import cv2
import numpy as np
import matplotlib.pyplot as plt
# 取得する色の範囲を指定する
lower_yellow = np.array([100,100,100])
upper_yellow = np.array([150,150,150])
cap = cv2.VideoCapture(0)
cascade = cv2.CascadeClassifier('TrainingAssistant/results/cascades/tegaki_maru2/cascade.xml') #分類器の指定
while(1):
# フレームを取得
re... |
991,460 | 2cf922d1ef305316909ba84801aff210ae8a2151 | import json
from sqlalchemy import Column, Integer, String, ForeignKey
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm.session import sessionmaker
from Pub.RabbitMQ import RabbitMQInfo
import sqlalchemy
from os import path
'''
sql config
'''
with open(pa... |
991,461 | dcb6372256401f63b4a4232bbee277b35a4e28e3 | from unittest import TestCase, main
from project.card.card import Card
from project.card.card_repository import CardRepository
from project.card.magic_card import MagicCard
class TestCardRepository(TestCase):
def setUp(self):
self.card_rep = CardRepository()
self.magic_card = MagicCard('A')
... |
991,462 | e4c7747d8e44af31e1c4ca446a4cc797e843e1ca | from abc import ABC
from typing import Dict
import motor.motor_asyncio
from application.main.config import settings
from application.main.infrastructure.database.db_interface import DataBaseOperations
from application.main.utility.config_loader import ConfigReaderInstance
class Mongodb(DataBaseOperations, ABC):
... |
991,463 | 17a8cd7204a5b0b802f95b0b1d0555b6847e0b13 | from math import sqrt
def prime_nums(n):
if type(n) != int:
raise TypeError()
if n < 0:
raise ValueError()
rslt = []
for x in range(0, n):
if is_prime(x):
rslt.append(x)
return rslt
"""
Based on.
Title: Prime Numbers
Author: James Conan
Date: N/A
Code version: Pseudocode
Availability: http://www.cs.uwc... |
991,464 | c50533e019f99748c66231c6d1518c2e23360a1e | #!/usr/bin/env python
import rospy
from nav_msgs.msg import Path
from geometry_msgs.msg import Twist, TwistStamped, PoseStamped
import roslib
import rospy
import math
import tf
import numpy as np
ROBOT_FRAME = 'base'
GOAL_THRES_POS = 0.2
GOAL_THRES_ANG = 0.2
FACE_GOAL_DIST = 1.0
def getYaw(quat):
_, _, yaw =... |
991,465 | 4adb4af4e30d98b5b056f18b97508978e08bb4d3 | from pyspark import SparkConf, SparkContext
conf=SparkConf().setMaster('local').setAppName('FriendsByAge')
sc=SparkContext(conf=conf)
def parseLine(line):
fields=line.split(',')
age=int(fields[2])
numFriends=int(fields[3])
return (age, numFriends)
lines=sc.textFile("file:///SparkCourse/fakef... |
991,466 | 34b82743396a5c8a898bd7272d112ecfec23b9f3 | """
:mod:`common` -- Common functions and classes for supporting FRBR Redis datastore
"""
__author__ = 'Jeremy Nelson'
import urllib2,os,logging
import sys,redis
import namespaces as ns
from lxml import etree
try:
import config
REDIS_HOST = config.REDIS_HOST
REDIS_PORT = config.REDIS_PORT
REDIS_DB = ... |
991,467 | 94fd5a7782d14b44a979d33a444b3c0675d4e446 | import itertools
n,k = map(int,input().split())
ab = [0]*n
for i in range(n):
ab[i] = input().split()
a = []
b = []
for i in range(n):
tmp1 = int(ab[i][0])
tmp2 = int(ab[i][1])
a.append(tmp1)
b.append(tmp2)
ab = zip(a,b)
ab = sorted(ab)
a,b = zip(*ab)
s = 0
for i in range(n):
s += int(b[i])
if s >= k:
... |
991,468 | 9ff030f2815a263074844d1cd74fce0d19d44b76 | import pygame as pg
from duchshund_walk import globals
from duchshund_walk.app_core import States
from duchshund_walk.messages import message_display
from duchshund_walk.settings import NICKNAME_MAX_LENGTH
from duchshund_walk.settings import WHITE
from duchshund_walk.settings import WORLD_HEIGH
from duchshund_walk.sett... |
991,469 | 4b615ac16099f42be5d47203fc43e4d46e82b8de | #!/opt/local/bin/python
import tkinter as tk
import tkinter.ttk as ttk
import sys
from random import randint
import threading
globstop = 0
mauvaisetage = False
portes_ouvertes = 0 # à 1 les portes sont complétement ouvertes, à 0 elles sont fermées
portes_bloquees = False
PORTES_UN_PEU_OUVERTES = 0.5 # à quelle pro... |
991,470 | e80e86bbcb76b248356d1cd2dc70949bdc0b1f92 | #!/usr/bin/python3
import os
import zipfile, tempfile
import click
import shutil
@click.command()
@click.argument('input', nargs=1, type=click.Path(exists=True, file_okay=True, dir_okay=False))
def main(input):
"""A small script that converts docx files to lyx using pandoc and tex2lyx.
A folder with the name of th... |
991,471 | 6e67635ac77004e464ecbb494107ca87018c3d11 | from fabric.api import *
env.hosts = ['192.168.33.10']
env.user = 'vagrant'
env.password = 'vagrant'
def package():
local('python setup.py sdist --format=gztar', capture=False)
def deploy():
dist = local('python setup.py --fullname', capture=True).strip()
put('dist/%s.tar.gz' % dist, '/tmp/myapp.tar.gz')
run... |
991,472 | 030213bef6a4611876018682579ab6b8af2f6aa1 | # -*- coding: utf-8 -*-
from zope.i18nmessageid import MessageFactory as ZMessageFactory
import warnings
_ = ZMessageFactory('plone')
def MessageFactory(*args, **kwargs):
# BBB Remove in Plone 5.2
warnings.warn(
"Name clash, now use '_' as usal. Will be removed in Plone 5.2",
DeprecationWarni... |
991,473 | 8a8f29658e6db4b0418dcf1a06d7ea5656d49ce9 | #！/usr/bin/python
# -*- coding: utf-8 -*-
import itertools
import time
#mylist = list(itertools.product([0,1,2,3,4,5,6,7,8,9,],repeat=5))
passwd = ("".join(x) for x in itertools.product("0123456789",repeat=3))
#print(mylist)
#print(len(mylist))
while True:
try:
time.sleep(0.5)
str = next(passwd)
... |
991,474 | ed3d3cebe7108b2054f8f2806767ca6152eac47b | #Author : Rohit
#license to : ABB Seden
'''56 sonar-scanner-4.6.0.2311-linux/bin/sonar-scanner -Dsonar.login=5b1bd1feaea303f4b6b40f68998849018b917332
57 sonar-scanner-4.6.0.2311-linux/bin/sonar-scanner -Dsonar.login=5b1bd1feaea303f4b6b40f68998849018b917332 -Dsonar.java.binaries=.
58 vim sonar-project.properties
59 s... |
991,475 | 57f88afe5d6918be27810c815b280682c77086b2 | # -*- coding: utf-8 -*-
"""
actions.py
:copyright: © 2019 by the EAB Tech team.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0... |
991,476 | ef86dcb590d54e95f8d6de436dde0575197447fd | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Created by wxk on 17-10-15 上午12:23
# Email="wangxk1991@gamil.com"
# Desc: 短信通知类
from src.Notify import Notify
class Sms(Notify):
pass |
991,477 | 3a69f68ba53cc795563304841dcf8b8049c15467 | # ___________________________________________________________________________
#
# Pyomo: Python Optimization Modeling Objects
# Copyright (c) 2008-2022
# National Technology and Engineering Solutions of Sandia, LLC
# Under the terms of Contract DE-NA0003525 with National Technology and
# Engineering Solutions of ... |
991,478 | 348ae5edf29acf1293ee9ea5e00d26dcfa4b6c61 | # Generated by Django 3.1.6 on 2021-06-03 18:35
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('banner', '0002_auto_20210603_0815'),
]
operations = [
migrations.CreateModel(
name='BannerSeen'... |
991,479 | 49a3ae6630dcb9d34e9d86bc2469ba1ed9b582f5 | from pymongo import MongoClient
from requests import post
client = MongoClient(API_mongoDB) #数据库地址
db = client['chatLog']
users = db['usercontacts']
for user in users.find(): # 遍历usercontacts文档，每次输出一个用户
userPhone = user['userPhone'] #提取用户手机号
userContacts = user['userContacts'] #提取userContacts中的信息，然后解析
c... |
991,480 | 3bda0448e95d1b18a6920df6d75e34759192ff8e |
abbreviations_map = {
'aca': [''],
'asme': ['american society of mechanical engineers'],
'ackerman union': ['au', 'ackerman'],
'afrikan student union': ['asu'],
'alpha gamma omega ucla': ['ago'],
'alpha kappa psi - ucla alpha upsilon chapter': ['akp'],
'alpha tau delta - gamma chapter': ['atd'],
'amer... |
991,481 | b677a829d1b0e1ae83713fc7db683ee16a5ca22e | import argparse
import cv2
import numpy as np
import torch
from facenet_pytorch.models.mtcnn import MTCNN
from omegaconf import OmegaConf
from tqdm import tqdm
import time
from pathlib import Path
from experiment import HairClassifier
from transforms.transform import get_infer_transform
from utils.infer_utils import ... |
991,482 | 435f0edf22db434c748a323ee62e5e9b46a140c2 | # -*- coding: utf-8 -*-
# Copyright (c) 2015-2019 Jan-Philip Gehrcke. See LICENSE file for details.
from __future__ import unicode_literals
from unittest import TestCase
from distutils import dir_util, file_util
from inspect import currentframe
import os
test_data_folder_path = os.path.join(os.path.dir... |
991,483 | 870b7b588cc3df622e09b6d7f12882a7304daac2 | #!/usr/bin/env python2
import signal
import logging
from programs import Program
from switches.base import SwitchProxy
from writer.base import WriterProxy
from manager.base import ManagerProxy
from misc.autobahnWebSocketBase import WebSocketBase
from conf.private import writer, switches, manager, switch_programs_file
... |
991,484 | cf8834e562f4f498e29c5c398ca7dbf0dfd941c4 | # -*- coding: utf-8 -*-
"""Main module."""
def simpleAddition(num1, num2):
return num1 + num2 |
991,485 | f02f427e11a1843917f3a40d28a9e5f8101819f7 | #run this by 'python3 manage.py runscript load_from_csv
import csv
from majorApp.models import News
def run():
fhand = open('data/test_data.csv')
reader = csv.reader(fhand)
News.objects.all().delete()
for row in reader:
print(row)
# news, created = News.objects.get_or_create(title_... |
991,486 | 6cd7ad096e1abb15a2bac8ecdbb0fc47cce70b47 | from datetime import datetime
def list_to_json(book_list):
size = len(book_list)
json = '{"book_list": {'
for index, book in enumerate(book_list):
if index == size - 1:
book_json = '"book": ' + book.to_json()
else:
book_json = '"book": ' + book.to_json() + ', '
... |
991,487 | 4be33ec39fb8e3ff4d5245d7b000400858826274 | #!/usr/bin/python
# Plot an image from a CSV file. xpix, ypix, iter.
# JM Wed 22 Nov 2017 21:39:59 GMT
import csv
from PIL import Image
from timeit import default_timer as timer
from lc import colour_list
import sys
import os
start = timer()
lenlc = len( colour_list )
rnum = 93
maxiter = 150
white ... |
991,488 | c11bf33e1d0daa539d6cf6a0e2e5a8cdda1e39a7 | import os
import re
import pandas as pd
import numpy as np
from firecloud import api as firecloud_api
import datetime
import glob
"""
_____ ___ ____ _____ ____ _ ___ _ _ ____ ____ _ _ ____ _ ____
| ___|_ _| _ \| ____/ ___| | / _ \| | | | _ \ / ___|| | | |/ ___| / \ | _ \
| |_ | || |... |
991,489 | 694ef27a90b8fc515517608104e6c1e23e416bb6 | x = lambda a, b: a + 1 + b
print(x(2, 3)) |
991,490 | 921e2072d270a66b5d0da39a40ed00ba3be53856 | import rclpy
from rclpy.node import Node
from contextlib import contextmanager
from functools import partial, total_ordering
from importlib import import_module
import queue
import socket
from typing import Any
import threading
import traceback
import time
from ros2relay.message_socket.message_socket import MessageSo... |
991,491 | 2d570b9ad381032d32b0f2afa7957d1c604bb054 | import threading
import time
class myThread(threading.Thread):
def __init__(self,s,name):
threading.Thread.__init__(self)
self.s=s
self.name=name
def run(self):
c, addr = self.s.accept()
while (True):
try:
msg = "server data"
da... |
991,492 | 7d2865faaf0d041cefae0b4b141871652de43dfc | """
https://github.com/openai/gym/wiki/Table-of-environments
https://github.com/openai/gym/tree/master/gym/envs -
check gym/gym/envs/__init__.py for solved properties (max_episode_steps, reward_threshold, optimum).
Solved: avg_score >= reward_threshold, over 100 consecutive trials.
"Unsolved environment" -... |
991,493 | 630b2bb65e1686cfd2e3782e219caa24056c892a | """
Permission Related Code
"""
from .helpers import *
from .imports import *
class StaffMember(BaseModel):
"""Represents a staff member in Fates List"""
name: str
id: Union[str, int]
perm: int
staff_id: Union[str, int]
async def is_staff_unlocked(bot_id: int, user_id: int):
return await re... |
991,494 | d89d454eca7ff2db6405b5539702046543a60dac | a,b = input().split()
c = len(set(list(a)))
b = len(set(list(b)))
if b == c:
print("yes")
else:
print("no")
|
991,495 | 378a85f3f2960c3f61aed8d79c09bf7acc9e3a16 | import numpy as np
import torch
import gym
import argparse
import os
import utils
import TD3
import kerbal_rl.env as envs
def generate_input(obs) :
mean_altitude = obs[1].mean_altitude
speed = obs[1].vertical_speed
dry_mass = obs[0].dry_mass
mass = obs[0].mass
max_thrust = obs[0].max_thrust
thrust = obs[0].t... |
991,496 | 015a82703bd5e83ae8d4baa835cf4dfc3cb9d648 | import json
import arrow
import logging
from ..parser.tconnect import TConnectEntry
from ..parser.nightscout import NightscoutEntry
logger = logging.getLogger(__name__)
def process_cgm_events(readingData):
data = []
for r in readingData:
data.append(TConnectEntry.parse_reading_entry(r))
retu... |
991,497 | 6ca2be7f4bf28f42e6dc9dc89f276f36225d0e99 | # Classify images of dogs & cats
# dataset is Kaggle's Dogs vs Cats
# First, clustering the SURF features for all images
# Second, represent each image by its feature counts of clusters (BOF)
# Finally, logistic regression to classify dog or cat |
991,498 | 31280b53a821644a1ba4a8b72599857a80c3b427 | # Filename: calc_ssXtorisons.py
# Author: Evelyne Deplazes
# Date: May 5, 2018
# Script to calculate the five torsion angles that are defined by the
# two residues that form a disulfide bbond (see below for defintion of
# torsion angles)
# the script relies on the definition of the disulfdie bonds by the keyword S... |
991,499 | f06972da07df5266400b718fb2f969c5e34a1459 | from functions import *
df, target = get_dataset()
X_train, X_test, y_train, y_test = train_test_split(df, target, test_size=0.33, random_state=42)
mean_value = np.mean(y_train)
print(mean_value)
y_pred_mean = [mean_value for _ in range(len(y_test))]
mean_squared_error(y_test, y_pred_mean, squared=False)
model = Ada... |
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